Matias Recchia is Co-Founder and CEO of Keyway, the AI- powered real estate investment manager.
If you’re a commercial real estate investor, there’s constant pressure to identify the best quality opportunities before competitor investors strike. From deal sourcing and underwriting to due diligence and closing, the process can be slow and manual despite a critical need for speed. The good news: This manual process is changing.
The advent of AI has transformed the deal sourcing landscape. Instead of relying solely on manual spreadsheets or brokers, investors can now leverage the power of AI to evaluate potential acquisition opportunities, analyze real-time market conditions and expedite due diligence. My company developed technology that analyzes properties and markets based on unbiased public data with the goal of determining a fair valuation for properties and accelerating the due diligence process to close faster. Here’s what we’ve learned:
How To Find Real Estate Deals
Finding real estate deals is one of the most challenging aspects of real estate investing. Most real estate listing websites have high-level information for various properties, but they fail to provide investors with granular data and insights that can be used to make better decisions. For example, how will this property perform over the next few years? How will this property impact my portfolio? How do I find off-market deals? A good AI tool can use AI and machine learning to help investors hone in on what really matters.
When evaluating tools, I recommend looking for a few specific features. The AI tool should:
• Analyze precedent transactions, zoning records, property performance and market dynamics to connect investment goals with target properties.
• Use predictive analytics to determine how a property will perform under a certain set of conditions. Rather than rely on brokers or landlords to supply this information, use only public data to ensure full transparency for stakeholders.
Increasingly, investors also want to customize their searches; static websites provide generic “search criteria” to input property features. However, with AI, investors can use a recommendation engine that adjusts preferences based on acceptances and rejections of properties to create a more tailored, customized property search process. This helps investors focus on properties that fit their buy box. At the same time, AI learns from user behavior, which creates a more interactive experience for investors.
How To Evaluate Markets
Real estate investors can no longer rely on incomplete broker reports or potentially biased word-of-mouth assertions to understand a specific market. Investors need to know more than “invest in Dallas.” They need a game plan to invest at the specific neighborhood level based on data-driven analytics. They need insights into the competitive landscape, rent growth, leasing velocity, amenities, new developments and multiple other factors to get a 360-degree view of the target market.
Look for tools that standardize unstructured data to compare properties easily across multiple metrics. This can help you determine if a property’s asking price is priced fairly. For example, if a comparable property around the corner has a similar square footage and amenity profile and charges 15% more rent, this could signal that a buyer could raise rents. Conversely, if the neighborhood indicates high turnover or poor real estate absorption rates, that could indicate a neighborhood to avoid.
How To Accelerate Due Diligence
Once you identify a target neighborhood and property, the real work begins. Due diligence and legal documents can jeopardize a deal. For larger assets, multiple lease documents (each with separate lease terms), tenant obligations and landlord obligations present serious risks for both buyers and sellers if not closely followed. Organizing these voluminous documents in a structured format can be a large undertaking. Further, missing a clause or misinterpreting a material contract provision can create serious financial or legal implications.
To address these challenges, AI and machine learning can be used to extract key information from leases and other important legal agreements in a more structured way. The result is lower legal costs, less manual work and fewer errors. For example, imagine organizing all rent increases or renewal options in a single location while also highlighting key tenant termination provisions for investors. Investors also need to understand whether the landlord or tenant is responsible for a particular expense. If managing a large portfolio, these respective responsibilities can vary by lease. With AI and machine learning at the helm, manual review can be replaced with automation, and buyers can quickly confirm that rent rolls match lease provisions.
Real estate investors today need more data, transparency and speed. Solutions that focus on deal sourcing, market evaluation and due diligence streamlining can offer powerful benefits to investors. We are still in the early stages of seeing what AI and machine learning can do, but the results are promising: less guesswork, fewer errors and more confident decisions.
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